The design of a digital integrated circuit is highly automated and the design period of the digital integrated circuit is thus greatly reduced. As a comparison, the design of an analog integrated circuit is mostly manual. Consequently, the design period of the analog integrated circuit is typically 2 or 3 times that of the digital integrated circuit. The design period of a hybrid integrated circuit is limited by the design period of the analog integrated circuit. The design period of the analog integrated circuit can be reduced by increasing the design automation of the analog integrated circuit. The design period of the hybrid integrated circuit can also be reduced. The design automation of the analog integrated circuit will lower the design cost and provide more competitive products.
Analog circuit migration is typically used in the design of the analog integrated circuit, which migrates a source circuit to a target circuit. The analog circuit migration typically includes optimization of parameter values of devices of an integrated circuit in a circuit level and physical optimization of positions and wirings of the devices of the integrated circuit in a layout level.
In the analog circuit migration, the first approach of circuit optimization includes the following work of a designer: setting parameter values of devices in accordance with prior knowledge, performing circuit simulation, and checking whether the design meets the design requirement or not. The steps of setting the parameter values, performing the circuit simulation and checking the design are repeated until properties of a target circuit approximates properties of a source circuit. The first approach of circuit optimization has the drawback that the optimization efficiency mainly relies on the designer's experience in designing the integrated circuit. The designer should well know variation of the performances of the circuit due to changes of the parameter values of the devices. Actually, the designer cannot well know the variation of the properties of the circuit due to the changes of the parameter values of the devices, when a scale and an integration level of the integrated circuit are increased. The design efficiency of the above approach will be very low.
In the analog circuit migration, the second approach of circuit optimization includes scanning parameter values of the devices and performing circuit simulation using a circuit simulator, and setting suitable parameter values of the devices in accordance with a result of the circuit simulation. The second approach is typically supplementary to the first approach. The second approach of circuit optimization has the drawback that only a limited number of parameters can be scanned. The designer needs to manually select the parameters to be scanned, determine a sequence of scanning the parameters, and set parameter values in accordance with the result of simulation. It is more and more difficult for the designer to manually select the parameters to be scanned, determine a sequence of scanning the parameters, and set parameter values, when the scale and the integration level of the integrated circuit are increased.
In the analog circuit migration, the third approach of circuit optimization includes randomly setting parameter values of the devices, performing circuit simulation or symbolic analysis to obtain performances of the circuit, controlling an optimization process globally to obtain optimal parameter values by optimization algorithm such as simulated annealing, genetic algorithm, and Particle Swarm Optimization (PSO), etc. The third approach of circuit optimization has the drawback that computational complexity is too large to be used in the circuit optimization of the analog integrated circuit with a large scale and a large complexity.
Actually, all of the first to third approaches of the circuit optimization have the drawback that computational complexity is too large to be used in the circuit optimization of the analog integrated circuit with a large scale and a large complexity.